Isaac Moradi, NASA’s Global Modeling and Assimilation Office (GMAO) and University of Maryland

28/07/2026 ore 11:00

CNR-ISAC, Bologna – meeting room online

Abstract

Accurate representation of precipitation and cloud processes remains a fundamental challenge in numerical weather prediction (NWP), particularly for high-impact weather events such as tropical cyclones. Although substantial progress has been made in improving track forecasts, prediction of storm intensity and internal structure continues to lag behind. These deficiencies are closely linked to the representation of key geophysical variables, including atmospheric moisture and hydrometeors, which play a critical role in governing the evolution of convection and precipitation.
Passive microwave observations from low Earth orbiting satellites provide valuable all-sky information on atmospheric temperature, water vapor, and precipitation; however, they generally provide layer-averaged information on cloud and precipitation properties. Active radar observations, such as those from the GPM Dual-frequency Precipitation Radar (DPR) and the EarthCARE Cloud Profiling Radar (CPR), further complement these measurements by providing detailed vertical structure of clouds and precipitation. However, the assimilation of radar observations remains limited due to challenges associated with forward operator accuracy, representation of microphysical processes, and deficiencies in the first-guess fields in cloudy and precipitating regions.
To address these challenges, the Community Radiative Transfer Model (CRTM) has been enhanced with a hydrometeor scattering database based on the Discrete Dipole Approximation (DDA), enabling physically consistent simulation of both passive microwave radiances and radar reflectivity. In addition, a radar forward operator has been incorporated into CRTM to support multi-frequency reflectivity calculations. These developments are being integrated within the JEDI data assimilation framework and evaluated in systems such as NASA GEOS and NOAA HAFS, demonstrating improved representation of precipitation, water vapor, and cloud structures, and ultimately contributing to enhanced forecasts of tropical cyclones and other high-impact weather events.

Bio

Dr. Isaac Moradi is a Research Scientist at the University of Maryland’s Earth System Science Interdisciplinary Center (ESSIC), with joint affiliations at NASA’s Global Modeling and Assimilation Office (GMAO) and NOAA’s Center for Satellite Applications and Research (STAR). He holds two Ph.D. degrees: one in Radio and Space Science from Chalmers University of Technology and another in Climatology and Environmental Planning from Khwarizmi University. His research focuses on radiative transfer modeling and the assimilation of satellite-based microwave and radar observations into numerical weather prediction systems.
Dr. Moradi has made substantial contributions to the development and advancement of the Community Radiative Transfer Model (CRTM), particularly in improving the simulation of satellite observations in the presence of clouds and precipitation. He has also played a key role in advancing satellite data assimilation capabilities within the Joint Effort for Data Assimilation Integration (JEDI) framework.
In addition to his research activities, Dr. Moradi has been actively engaged in academic and professional service, including service on the University of Maryland Senate and its Executive Committee since 2018. He is also an active member of the American Meteorological Society (AMS), where he serves on the Committee on Atmospheric Radiation, the Forecast Improvement Group (FIG), and the Committee on Radio Frequency Allocations.

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